Not applicable.
(1) Field of The Invention
The present invention generally relates to an apparatus and method for reducing the noise emanating from near-ocean surface sources without reducing the signal level of a target of interest.
(2) Description of the Prior Art
There have been several prior art methods developed to solve the sonar problem of reducing noise from a loud, near-surface noise source while maintaining the signal level of signals produced by the target of interest (TOI). As used herein, the phrases xe2x80x9cnear-surface noise sourcexe2x80x9d or xe2x80x9cnear-surface sourcexe2x80x9d refer to an object (e.g., ship) that is primarily located on or near the ocean surface. An intensive effort has been directed to the area of adaptive beamforming as evident by the development of the well known minimum variance distortion response (MVDR) algorithms. For ideal ocean conditions, when the spatial coherence of the acoustic field is known exactly, MVDR algorithms are optimum in minimizing the total noise field while maintaining the TOI""s signal level constant. However, there is only a finite time to estimate the acoustic field spatial coherence. Furthermore, errors between the actual and estimated acoustic field spatial coherence degrade the performance of MVDR algorithms rapidly because MVDR algorithms are highly non-linear MVDR algorithms require the calculation of the inverse matrix for the acoustic field spatial coherence spectral matrix (CSM). Small errors in the estimate of CSM can propagate to very large errors in the estimate of the inverse matrix of CSM. The CSM is defined as the matrix of all cross product pairs of individual hydrophone time series Fast Fourier Transforms (FFTs). The CSM is described in detail in commonly owned U.S. Pat. No. 5,481,505. Therefore, MVDR algorithms are not robust in realistic open ocean environments, and are severely degraded when short averaging times must be used in tactical sonar systems.
A second class of prior art algorithms developed to address the aforementioned problem is referred to as the WHISPR family of processing algorithms. Although the number of different WHISPR related algorithms is relatively large, these algorithms rely on one physical principle: the acoustic time series of a near-surface noise source has a significantly greater time variance than the acoustic time series from a submerged target of interest due to the Lloyd""s Mirror effect and several other causes. The Lloyd""s Mirror effect is a highly variable interference pattern as a function of range between the source and receiver. The interference pattern is caused by the direct path and ocean surface-reflected paths between the source and receiver, and the fact that the amplitude of the fluctuations is significantly greater for near-surface sources than for deeper sources. In fact, a source that is more than two acoustic wavelengths in depth below the ocean""s surface is said to be acoustically decoupled from the ocean""s surface and is not subject to large acoustic time series variations in level due to Lloyd""s Mirror interference. Other factors recognized by WHISPR algorithms are the relatively larger time fluctuations in energy received from near-surface sources. These fluctuations are caused by several factors, such as rapid change in propeller source depth as surface ships travel through ocean waves, or the cavitation of surface ships near the blades of their propellers due to high speeds and shallow depths.
Although WHISPR has shown some promise on selected acoustic data sets, it has never been developed into a real time system because it is not robust in real ocean environments. Specifically, time variability alone is not sufficiently robust to consistently reduce noise relative to the signal from the deeper TOI. Surface ships can produce a more stable signal if: (i) the ships are relatively large and have a deep draft, (ii) the ocean surface is rough, (iii) a bubble layer on the ocean surface scatters the reflected path from its spectral reflection, and (iv) the near-surface sound speed profile is significantly upward or downward refracting so that straight line propagation assumed by the Lloyd""s Mirror effect is violated. There are other factors that contribute to a surface ship""s ability to produce a relatively more stable signal. The aforementioned factors have prevented WHISPR from being developed into a robust, real time sonar algorithm, although it has been shown to perform well on carefully selected data sets that corresponded to conditions that were well suited for WHISPR.
Although there are other prior art noise reduction techniques, the MVDR and WHISPR algorithms have been the most commonly used.
What is needed is a new and improved noise reduction technique that addresses the inefficiencies of the aforementioned prior art noise reduction techniques.
The present invention is directed to, a method for significantly reducing the acoustic noise from near-surface sources using an array processing technique that utilizes Multiple Signal Classification (MUSIC) beamforming and the Lloyd""s Mirror interference pattern at very low frequencies. Noise from nearby near-surface sources, such as merchant ships, super tankers, fishing trawlers, seismic profiling platforms, or other sources near the ocean surface can significantly interfere with the detection and tracking of a quiet target-of-interest (TOI) located well below the ocean surface. The present invention reduces the noise of the near-surface sources without degrading the signal level and quality of the TOI. The present invention utilizes a unique application of the MUSIC beamforming process to separate the noise and signal subspace. Next, eigenvalue beamforming is used to reduce narrowband energy in selected frequency bins wherein the near-surface noise is radiating. Next, predetermined frequency and magnitude variance parameters are used to eliminate broadband noise emanating from the near-surface sources.